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1دورية أكاديمية
مصطلحات موضوعية: Natural sciences
الوصف: The acts of speaking and singing are different phenomena displaying distinct characteristics. The classification and distinction of these voice acts is vastly approached utilizing voice audio recordings and microphones. The use of audio recordings, however, can become challenging and computationally expensive due to the complexity of the voice signal. The research presented in this paper seeks to address this issue by implementing a deep learning classifier of speaking and singing voices based on bioimpedance measurement in replacement of audio recordings. In addition, the proposed research aims to develop a real-time voice act classification for the integration with voice-to-MIDI conversion. For such purposes, a system was designed, implemented, and tested using electroglottographic signals, Mel Frequency Cepstral Coefficients, and a deep neural network. The lack of datasets for the training of the model was tackled by creating a dedicated dataset 7200 bioimpedance measurement of both singing and speaking. The use of bioimpedance measurements allows to deliver high classification accuracy whilst keeping low computational needs for both preprocessing and classification. These characteristics, in turn, allows a fast deployment of the system for near-real-time applications. After the training, the system was broadly tested achieving a testing accuracy of 92% to 94%.
وصف الملف: application/pdf
العلاقة: https://repository.uwl.ac.uk/id/eprint/9974/7/A.1-s2.0-S0892199723001200-main.pdfTest; Donati, Eugenio orcid:0000-0002-0048-1858 , Chousidis, Christos, Ribeiro, Henrique De Melo and Russo, Nicola (2023) Classification of Speaking and Singing Voices Using Bioimpedance Measurements and Deep Learning. Journal of Voice, 2023. ISSN 0892-1997 (In Press)
الإتاحة: https://doi.org/10.1016/j.jvoice.2023.03.018Test
https://repository.uwl.ac.uk/id/eprint/9974Test/
https://www.sciencedirect.com/science/article/pii/S0892199723001200?via%3DihubTest
https://repository.uwl.ac.uk/id/eprint/9974/7/A.1-s2.0-S0892199723001200-main.pdfTest -
2رسالة جامعية
المؤلفون: Chousidis, Christos
مرشدي الرسالة: Nilavalan, R.; Hadjinicolaou, M.; Karayiannis, T.
مصطلحات موضوعية: 621.382, Audio networking, Modified MAC, CTS-to -self, EBNA algozithm, Audio over IP (AoIP)
الوصف: Audio networking is a rapidly increasing field which introduces new exiting possibilities for the professional audio industry. When well established, it will drastically change the way live sound systems will be designed, built and used. Today's networks have enough bandwidth that enables them to transfer hundreds of high quality audio channels, replacing analogue cables and intricate installations of conventional analogue audio systems. Currently there are many systems in the market that distribute audio over networks for live music and studio applications, but this technology is not yet widespread. The reasons that audio networks are not as popular as it was expected are mainly the lack of interoperability between different vendors and still, the need of a wired network infrastructure. Therefore, the development of a wireless digital audio networking system based on the existing widespread wireless technology is a major research challenge. However, the ΙΕΕΕ 802.11 standard, which is the primary wireless networking technology today, appears to be unable to handle this type of application despite the large bandwidth available. Apart from the well-known drawbacks of interference and security, encountered in all wireless data transmission systems, the way that ΙΕΕΕ 802.11 arbitrates the wireless channel access causes significantly high collision rate, low throughput and long overall delay. The aim of this research was to identify the causes that impede this technology to support real time wireless audio networks and to propose possible solutions. Initially the standard was tested thoroughly using a data traffic model which emulates a multi-channel real time audio environment. Broadcasting was found to be the optimal communication method, in order to satisfy the intolerance of live audio, when it comes to delay. The results were analysed and the drawback was identified in the hereditary weakness of the IEEE 802.11 standard to manage broadcasting, from multiple sources in the same network. To resolve this, a series of modifications was proposed for the Medium Access Control algorithm of the standard. First, the extended use of the "CTS-to-Self" control message was introduced in order to act as a protection mechanism in broadcasting, similar to the RTC/CTS protection mechanism, already used in unicast transmission. Then, an alternative "random backoff" method was proposed taking into account the characteristics of live audio wireless networks. For this method a novel "Exclusive Backoff Number Allocation" (EBNA) algorithm was designed aiming to minimize collisions. The results showed that significant improvement in throughput can be achieved using the above modifications but further improvement was needed, when it comes to delay, in order to reach the internationally accepted standards for real time audio delivery. Thus, a traffic adaptive version of the EBNA algorithm was designed. This algorithm monitors the traffic in the network, calculates the probability of collision and accordingly switches between classic IEEE 802.11 MAC and EBNA which is applied only between active stations, rather than to all stations in the network. All amendments were designed to operate as an alternative mode of the existing technology rather as an independent proprietary system. For this reason interoperability with classic IEEE 802.11 was also tested and analysed at the last part of this research. The results showed that the IEEE 802.11 standard, suitably modified, is able to support multiple broadcasting transmission and therefore it can be the platform upon which, the future wireless audio networks will be developed.
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3مؤتمر
المؤلفون: Tomaszewska, Julia Z., Chousidis, Christos, Donati, Eugenio
مصطلحات موضوعية: Computing
الوصف: Sound recording and processing techniques can be used in designing diagnostic solutions for a variety of medical conditions related to the respiratory system. In this spectrum, cough monitoring for chronic or seasonal conditions is a significant medical practice. In this paper, a precise cough identification and monitoring system is presented. The system is utilising a convolutional neural network as a feature extraction algorithm and classification system. Including several functions of loading the audio data into the system and converting it into a set of spectrograms, as well as the pre-segmentation stage function, the model retains its relatively low-complexity, which allows accelerating the learning process, also enhanced using dropout. Due to limited audio data available, the dataset dimension was established at 600 samples, split into two equal-numbered groups – 300 samples of “cough” samples, and 300 of “non-cough” samples. The validation accuracy (thus the percentage of samples labelled correctly by the system during the validation process) yielded over 84%, suggesting that this can be a successful cough detection method for future medical applications and devices, such as potential respiratory system condition diagnostic tool.
وصف الملف: application/pdf
العلاقة: https://repository.uwl.ac.uk/id/eprint/11310/1/MeMeA2022_Julia.pdfTest; Tomaszewska, Julia Z., Chousidis, Christos orcid:0000-0003-3762-8208 and Donati, Eugenio orcid:0000-0002-0048-1858 (2022) Sound-Based Cough Detection System using Convolutional Neural Network. In: 2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA), 22-24 Jun 2022, Messina, Italy.
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4دورية أكاديمية
المؤلفون: Donati, Eugenio, Chousidis, Christos
مصطلحات موضوعية: Digital signal processing, Intelligent systems, Sound engineering, Music/audio technology
الوصف: Voice-to-MIDI real-time conversion is a challenging problem that comes with a series of obstacles and complications. The main issue is the tracking of the human voice pitch. Extracting the voice fundamental frequency can be inaccurate and highly computationally exacting due to the spectral complexity of voice signals. In addition, on account of microphone usage, the presence of environmental noise can further affect voice processing. An analysis of the current research and status of the market shows a plethora of voice-to-MIDI implementations revolving around the processing of audio signals deriving from microphones. This paper addresses the above-mentioned issues by implementing a novel experimental method where electroglottography is employed instead of microphones as a source for pitch-tracking. In the proposed system, the signal is processed and converted through an embedded hardware device. The use of electroglottography improves both the accuracy of pitch evaluation and the ease of voice information processing; firstly, it provides a direct measurement of the vocal folds' activity and, secondly, it bypasses the interferences caused by external sound sources. This allows the extraction of a simpler and cleaner signal that yields a more effective evaluation of the fundamental frequency during phonation. The proposed method delivers a faster and less computationally demanding conversion thus in turn, allowing for an efficacious real-time voice-to-MIDI conversion.
وصف الملف: application/pdf
العلاقة: https://repository.uwl.ac.uk/id/eprint/9005/7/Donati_and_Chousidis_2022_j.neuri._Electroglottography_based_real-time_voice-to-MIDI_controller.pdfTest; Donati, Eugenio orcid:0000-0002-0048-1858 and Chousidis, Christos orcid:0000-0003-3762-8208 (2022) Electroglottography based real-time voice-to-MIDI controller. Neuroscience Informatics, 2 (2). p. 100041. ISSN 2772-5286
الإتاحة: https://doi.org/10.1016/j.neuri.2022.100041Test
https://repository.uwl.ac.uk/id/eprint/9005Test/
https://repository.uwl.ac.uk/id/eprint/9005/7/Donati_and_Chousidis_2022_j.neuri._Electroglottography_based_real-time_voice-to-MIDI_controller.pdfTest -
5دورية أكاديمية
المؤلفون: Tomaszewska, Julia Z., Młyńczak, M., Georgakis, Apostolos, Chousidis, Christos, Ładogórska, M., Kukwa, W.
مصطلحات موضوعية: Computing
الوصف: Background: Heart rate is an essential diagnostic parameter indicating a patient’s condition. The assessment of heart rate is also a crucial parameter in the diagnostics of various sleep disorders, including sleep apnoea, as well as sleep/wake pattern analysis. It is usually measured using an electrocardiograph (ECG)—a device monitoring the electrical activity of the heart using several electrodes attached to a patient’s upper body—or photoplethysmography (PPG). Methods: The following paper investigates an alternative method for heart rate detection and monitoring that operates on tracheal audio recordings. Datasets for this research were obtained from six participants along with ECG Holter (for validation), as well as from fifty participants undergoing a full night polysomnography testing, during which both heart rate measurements and audio recordings were acquired. Results: The presented method implements a digital filtering and peak detection algorithm applied to audio recordings obtained with a wireless sensor using a contact microphone attached in the suprasternal notch. The system was validated using ECG Holter data, achieving over 92% accuracy. Furthermore, the proposed algorithm was evaluated against whole-night polysomnography-derived HR using Bland-Altman’s plots and Pearson’s Correlation Coefficient, reaching the average of 0.82 (0.93 maximum) with 0 BPM error tolerance and 0.89 (0.97 maximum) at ±3 BPM. Conclusions: The results prove that the proposed system serves the purpose of a precise heart rate monitoring tool that can conveniently assess HR during sleep as a part of a home-based sleep disorder diagnostics process.
وصف الملف: application/pdf
العلاقة: https://repository.uwl.ac.uk/id/eprint/11311/1/diagnostics-v3_Julia.pdfTest; Tomaszewska, Julia Z., Młyńczak, M., Georgakis, Apostolos, Chousidis, Christos orcid:0000-0003-3762-8208 , Ładogórska, M. and Kukwa, W. (2022) Automatic Heart Rate Detection during Sleep Using Tracheal Audio Recordings from Wireless Acoustic Sensor. MDPI Diagnostics.
الإتاحة: https://repository.uwl.ac.uk/id/eprint/11311Test/
https://www.mdpi.com/2075-4418/13/18/2914#:~:text=The%20study%20applied%20a%20deep,of%205%20beats%20per%20minuteTest.
https://repository.uwl.ac.uk/id/eprint/11311/1/diagnostics-v3_Julia.pdfTest -
6دورية أكاديمية
المؤلفون: Tomaszewska, Julia Zofia, Młyńczak, Marcel, Georgakis, Apostolos, Chousidis, Christos, Ładogórska, Magdalena, Kukwa, Wojciech
المصدر: Diagnostics (2075-4418); Sep2023, Vol. 13 Issue 18, p2914, 13p
مصطلحات موضوعية: HEART beat, SOUND recordings, HEART rate monitors, HEART rate monitoring, POLYSOMNOGRAPHY, SLEEP apnea syndromes, PHOTOPLETHYSMOGRAPHY
مستخلص: Background: Heart rate is an essential diagnostic parameter indicating a patient's condition. The assessment of heart rate is also a crucial parameter in the diagnostics of various sleep disorders, including sleep apnoea, as well as sleep/wake pattern analysis. It is usually measured using an electrocardiograph (ECG)—a device monitoring the electrical activity of the heart using several electrodes attached to a patient's upper body—or photoplethysmography (PPG). Methods: The following paper investigates an alternative method for heart rate detection and monitoring that operates on tracheal audio recordings. Datasets for this research were obtained from six participants along with ECG Holter (for validation), as well as from fifty participants undergoing a full night polysomnography testing, during which both heart rate measurements and audio recordings were acquired. Results: The presented method implements a digital filtering and peak detection algorithm applied to audio recordings obtained with a wireless sensor using a contact microphone attached in the suprasternal notch. The system was validated using ECG Holter data, achieving over 92% accuracy. Furthermore, the proposed algorithm was evaluated against whole-night polysomnography-derived HR using Bland-Altman's plots and Pearson's Correlation Coefficient, reaching the average of 0.82 (0.93 maximum) with 0 BPM error tolerance and 0.89 (0.97 maximum) at ±3 BPM. Conclusions: The results prove that the proposed system serves the purpose of a precise heart rate monitoring tool that can conveniently assess HR during sleep as a part of a home-based sleep disorder diagnostics process. [ABSTRACT FROM AUTHOR]
: Copyright of Diagnostics (2075-4418) is the property of MDPI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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7دورية أكاديمية
المؤلفون: Chousidis, Christos, Ioana, Pisica, Zhengwen, Huang
مصطلحات موضوعية: Computer networking, Electrical and electronic engineering, Sound engineering
الوصف: The use of network infrastructures to replace conventional professional audio systems is a rapidly increasing field which is expected to play an important role within the professional audio industry. Currently, the market is dominated by numerous proprietary protocols which does not allowing interoperability and does not promote the evolution on this sector. Recent standardization actions are intending to resolve this issue excluding however the use of wireless networks. Existing wireless networking technologies are considered unsuitable for supporting real-time audio networks, not because of lack of bandwidth but due to their inefficient congestion control mechanisms in broadcasting. In this paper, we propose an amendment of the IEEE 802.11 MAC that improves the performance of the standard when is used for real-time audio data delivery. The proposed amendment is based on two innovative ideas. First, it provides a protection mechanism for broadcasting and second, replaces the classic congestion control mechanism, based in random backoff, with an alternative traffic adaptive algorithm, designed to minimize collisions. The proposed MAC is able to operate as an alternative mode, allowing regular Wi-Fi networks to coexist and interoperate efficiently with audio networks, with the last ones being able to be deployed over existing wireless network infrastructures.
وصف الملف: application/pdf
العلاقة: https://repository.uwl.ac.uk/id/eprint/6133/1/Chousidis_Ioana_and_Zhengwen_JNSM_2019_A_modified_IEEE_802.11_MAC_for_optimizing_broadcasting_in_wireless_audio_networks.pdfTest; Chousidis, Christos orcid:0000-0003-3762-8208 , Ioana, Pisica and Zhengwen, Huang (2019) A modified IEEE 802.11 MAC for optimizing broadcasting in wireless audio networks. Journal of Network and Systems Management, 28 (1). pp. 58-80. ISSN 1064-7570
الإتاحة: https://doi.org/10.1007/s10922-019-09501-3Test
https://repository.uwl.ac.uk/id/eprint/6133Test/
https://repository.uwl.ac.uk/id/eprint/6133/1/Chousidis_Ioana_and_Zhengwen_JNSM_2019_A_modified_IEEE_802.11_MAC_for_optimizing_broadcasting_in_wireless_audio_networks.pdfTest -
8مؤتمر
المصدر: 2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)
الإتاحة: https://doi.org/10.1109/memea54994.2022.9856512Test
http://xplorestaging.ieee.org/ielx7/9855895/9856402/09856512.pdf?arnumber=9856512Test -
9مؤتمر
المؤلفون: Donati, Eugenio, Chousidis, Christos
المصدر: 2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)
الإتاحة: https://doi.org/10.1109/memea54994.2022.9856413Test
http://xplorestaging.ieee.org/ielx7/9855895/9856402/09856413.pdf?arnumber=9856413Test -
10دورية أكاديمية
المساهمون: National Fundamental Research Program (973) of China, Science and Technology Commission of Shanghai Municipality, European Union’s Horizon 2020 research and innovation programme
المصدر: IEEE Transactions on Evolutionary Computation ; volume 22, issue 5, page 792-804 ; ISSN 1089-778X 1089-778X 1941-0026
الإتاحة: https://doi.org/10.1109/tevc.2017.2771445Test
http://xplorestaging.ieee.org/ielx7/4235/8478014/08187687.pdf?arnumber=8187687Test
النص الكامل